Single cell RNA-seq, a.k.a. Data exploration has probably never been so important - hidden gems (hypotheses, findings) come out only via extensive (and proper) exploration.
- this is a time consuming task
- often needed iterations and clever subsetting + linked information across plots
- how did I do this plot?
A few months, and about 1000 commits later…
logo, rafiki, quick vid/demo
scRNA-seq: genes * cells - Aim: Identification of cell subpopulations, description of developmental trajectories, dimension reduction
iSEE, interactive SummarizedExperiment/SingleCellExperiment Explorer: concept made in December 2017 @Bioc conference (joint work with Aaron Lun, Charlotte Soneson, Kevin Rue-Albrecht)